DocumentCode :
1612639
Title :
New swing-blocking methods for digital distance protection using Support Vector Machine
Author :
Kampeerawat, W. ; Buangam, W. ; Chusanapiputt, S.
Author_Institution :
Dept. of Electr. Power Eng., Mahanakorn Univ. of Technol., Bangkok, Thailand
fYear :
2010
Firstpage :
1
Lastpage :
6
Abstract :
This paper presents a method for power swing and fault diagnosis of power system based on Support Vector Machine (SVM) classifier. The method adopts Least Square Support Vector Machine (LS-SVM) classifier to identify the power swing and fault types. The power swing blocking elements are based on monitor the rate of change of the impedance, the power swing center voltage, the positive current and zero sequence component. The process of training the LS-SVM using a K-folded cross validation process for determining the values of parameter σ and parameter λ in RBF kernel parameter that will give minimum classification error. The proposed method can successfully detect power swing and provide power swing blocking for accurate distance protection during power swing.
Keywords :
fault diagnosis; power system faults; power system protection; support vector machines; K-folded cross validation process; digital distance protection; fault diagnosis; least square support vector machine classifier; power swing blocking elements; power system; swing-blocking methods; Circuit faults; Fault detection; Impedance; Support vector machine classification; Testing; Training; Distance Relay; Least Square Support Vector Machine; Power Swing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power System Technology (POWERCON), 2010 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4244-5938-4
Type :
conf
DOI :
10.1109/POWERCON.2010.5666525
Filename :
5666525
Link To Document :
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